Immunogenomic features of radiologically distinctive nodules in multiple primary lung cancer.

OBJECTIVES: To provide molecular and immunological attributes mechanistic insights for the management of radiologically distinctive multiple primary lung cancer (MPLC). METHODS: The Bulk RNA-seq data of MPLC were obtained from our center. The Bulk RNA-seq data and CT images of patients with single primary lung cancer (SPLC) were obtained from GSE103584. Immune infiltration algorithms were performed to investigate the disparities in the immunological microenvironment between the two groups. Single-cell gene analysis was used to explore immune cells composition and communication relationships between cells in MPLC. RESULTS: In MPLC, 11 pure ground-glass opacity nodules (pGGN) and 10 mixed GGN (mGGN) were identified, while in SPLC, the numbers were 18 pGGN and 22 mGGN, respectively. In MPLC, compared to pGGN, mGGN demonstrated a significantly elevated infiltration of CD8+ T cells. Single-cell gene analysis demonstrated that CD8+ T cells play a central role in the signaling among immune cells in MPLC. The transcription factors including MAFG, RUNX3, and TBX21 may play pivotal roles in regulation of CD8+ T cells. Notably, compared to SPLC nodules for both mGGN and pGGN, MPLC nodules demonstrated a significantly elevated degree of tumor-infiltrating immune cells, with this difference being particularly pronounced in mGGN. There was a positive correlation between the proportion of immune cells and consolidation/tumor ratio (CTR). CONCLUSIONS: Our findings provided a comprehensive description about the difference in the immune microenvironment between pGGN and mGGN in early-stage MPLC, as well as between MPLC and SPLC for both mGGN and pGGN. The findings may provide evidence for the design of immunotherapeutic strategies for MPLC.

Global, Regional, and National Burdens of Hearing Loss for Children and Adolescents from 1990 to 2019: A Trend Analysis.

This study presents a comprehensive analysis of global, regional, and national trends in the burden of hearing loss (HL) among children and adolescents from 1990 to 2019, using data from the Global Burden of Disease study. Over this period, there was a general decline in HL prevalence and years lived with disability (YLDs) globally, with average annual percentage changes (AAPCs) of -0.03% (95% uncertainty interval [UI], -0.04% to -0.01%; p = 0.001) and -0.23% (95% UI, -0.25% to -0.20%; p < 0.001). Males exhibited higher rates of HL prevalence and YLDs than females. Mild and moderate HL were the most common categories across all age groups, but the highest proportion of YLDs was associated with profound HL [22.23% (95% UI, 8.63%-57.53%)]. Among females aged 15-19 years, the prevalence and YLD rates for moderate HL rose, with AAPCs of 0.14% (95% UI, 0.06%-0.22%; p = 0.001) and 0.13% (95% UI, 0.08%-0.18%; p < 0.001). This increase is primarily attributed to age-related and other HL (such as environmental, lifestyle factors, and occupational noise exposure) and otitis media, highlighting the need for targeted research and interventions for this demographic. Southeast Asia and Western Sub-Saharan Africa bore the heaviest HL burden, while High-income North America showed lower HL prevalence and YLD rates but a slight increasing trend in recent years, with AAPCs of 0.13% (95% UI, 0.1%-0.16%; p < 0.001) and 0.08% (95% UI, 0.04% to 0.12%; p < 0.001). Additionally, the analysis revealed a significant negative correlation between sociodemographic index (SDI) and both HL prevalence (r = -0.74; p < 0.001) and YLD (r = -0.76; p < 0.001) rates. However, the changes in HL trends were not significantly correlated with SDI, suggesting that factors beyond economic development, such as policies and cultural practices, also affect HL. Despite the overall optimistic trend, this study emphasizes the continued need to focus on specific high-risk groups and regions to further reduce the HL burden and enhance the quality of life for affected children and adolescents.

Selective and sensitive detection of dimethyl phthalate in water using ferromagnetic nanomaterial-based molecularly imprinted polymers and SERS.

To overcome the complicated pretreatment, low selectivity and low sensitivity detection associated with the detection of dimethyl phthalate (DMP), this study synthesized ferromagnetic nanomaterials that coupled with surface enhanced Raman scattering (SERS) and molecular imprinting polymers (MIPs). The pretreatment process can be simplified by ferromagnetic nanomaterials, then Fe3O4@SiO2@Ag@MIPs selectively adsorbing DMP can be achieved, and SERS can be applied for DMP detection with high sensitivity. As a control, the non-imprinted polymers (NIPs) Fe3O4@SiO2@Ag@NIPs were synthesized. Adsorption experiments results showed that the saturation adsorption amounts of Fe3O4@SiO2@Ag@MIPs is 36.74 mg/g with 40 mg/L DMP and Fe3O4@SiO2@Ag@NIPs is 17.45 mg/g. For DMP, Fe3O4@SiO2@Ag@MIPs have a greater affinity. In addition, after seven adsorption-desorption cycles the Fe3O4@SiO2@Ag@MIPs are reusable with approximately a 9.8 % loss in adsorption capacity. With an 8.7 × 10-9 M detection limit, DMP detection was performed by SERS, which revealed that the Raman intensities of the associated characteristic peak were linearly proportional to the DMP concentrations. As a result, the recovery rate of the testing artificial water varied from 87.9 % to 117 %. These outcomes show that the suggested technique for finding DMP in actual water samples is practical.

Size and isotope analysis of individual nanoparticles by multi-collector ICP-MS using "event-triggered signal capture" with a high-speed oscilloscope.

Accurate quantitative elemental and isotope analysis of nanoparticles at the single-particle level is crucial for better understanding their origin, properties and behaviors. Single particle inductively coupled plasma-mass spectrometry (spICP-MS) has emerged as a promising technique for nanoparticle analysis. However, challenges persist in obtaining accurate and consistent element profiles and ratios for small-sized nanoparticles by conventional quadrupole (QMS) or time-of-flight mass analyzers (TOF-MS) due to their low level and transient nature. In this paper, we present a novel analytical method for single nanoparticle analysis using multiple collector ICP-MS (MC-ICP-MS) combined with a modern high-speed digital oscilloscope. The single particle events are acquired using an "event-triggered signal capture" (ETSC) technique, which enables the simultaneously capture and visualization of multiple isotopes of transient individual particle profiles with nanosecond time resolution. This greatly facilitates precise and efficient analysis of nanoparticles. The minimum detectable particle size is calculated to be as small as 8 nm (∼1 ag 109Ag) for AgNPs. Based on the 109/107Ag ratios obtained from 2000 particles, the precisions of 109/107Ag ratio measurements on 20 nm, 40 nm, 60 nm, 80 nm and 100 nm were approximately 0.086 (SD), 0.063 (SD), 0.051 (SD), 0.040 (SD), and 0.029 (SD), which is limited by counting statistics of the isotopic signals. Furthermore, the achieved standard error of 109/107Ag can be reduced to sub-permil level (0.7 ‰) even for the measurement of 20 nm AgNPs (N = 17,000). These results demonstrate that the ETSC provides a unique method for isotope analysis of single particles, holding great potential for enhancing our understanding of nanoparticles.

Quantitative assessment of inflammation and evaluation of spatial heterogeneity for non-alcoholic fatty liver disease in mice based on iron-adjustive T1.

Background: A sensitive and non-invasive method is necessary to diagnose non-alcoholic fatty liver disease (NAFLD). We explored the iron-adjustive T1 (aT1) ability to quantify the degree of liver inflammation and evaluate the spatial heterogeneity. Methods: Male C57BL/6J mice were randomly categorized as the NAFLD model (n=40), NAFLD-related liver cirrhosis model (n=20), and normal mice (n=10). T1 and T2* maps were acquired using a 3.0T scanner of magnetic resonance imaging (MRI) and aT1 maps through post-processing corrected iron's effect on T1 using T2*. Pathological changes in the left and right liver lobes were assessed using the Non-alcoholic Steatohepatitis-Clinical Research Network scoring system, though hepatic ballooning lesion were rare in models. Spearman's and partial correlation analyses were used to evaluate correlations, and the receiver operating characteristic curve was used to analyze the diagnostic performance. Results: aT1 was highly correlated with NAFLD activity score (NAS) (r=0.747, P<0.001) but not with the fibrosis stage when adjusted by NAS (r=-0.135, P=0.147). The area under the curve (AUC) of the aT1 value distinguishing groups with 0< NAS <4 and NAS ≥4 was 0.802. On analyzing the histogram features of aT1, the entropy, interquartile range, range, and variance were significantly different between the groups with 0< NAS <4 and NAS ≥4 (P<0.05). The entropy was the risk factor of NAS ≥4. Conclusions: aT1 could help evaluate the inflammatory activity in NAFLD mice unaffected by mild fibrosis, and the higher the degree of inflammation, the higher the heterogeneity of the aT1 map.

One-step fabrication of flexible polyamide@Ag-dodecanethiol membranes for highly sensitive SERS detection of thiram.

The surface-enhanced Raman scattering (SERS) is an effective spectral technology based on Raman scattering, but in practice, the commonly used SERS substrates suffer from low sensitivity and poor stability. In order to overcome these limitations, the SERS substrates were prepared from hydrophobic modification of dodecanethiol (C12) coupled with a flexible substrate, which was then used for pesticides detection in water. A flexible PA@Ag-C12 substrate with surface functionalization has been obtained. This work aims to investigate the self-assembly of Ag NPs modified with C12 onto polyamide (PA) membranes. Initially, transmission electron microscopy and scanning electron microscopy were used to analyze the substrate's morphology. Then with the help of an energy-dispersive spectrometer, sulfur content of C12-modified Ag NPs was analyzed. In order to determine the hydrophobicity of the modified Ag NPs, the contact angle was used. The results indicate that the gap between Ag NPs on PA membrane can be effectively controlled in order to prevent Ag NPs from aggregating. Furthermore, the finite-difference time-domain analysis indicated that the PA@Ag-C12 substrate exhibited a stronger electromagnetic enhancement effect than the PA@Ag substrate. By reducing NPs gaps on the PA membrane, the number of 'hot spots' increased, and the SERS performance of the substrate was improved as a result. According to the results of this study, this method can greatly reduce the manufacturing costs and time costs of the SERS substrate while maintaining the original uniformity. The SERS performance of PA@Ag-C12 was found to be three orders of magnitude better than that of PA@Ag direct self-assembled substrate, and the detection limit for Rhodamine 6G (R6G) was approximately 8.47 × 10-14M. On the basis of the PA@Ag-C12 substrate, thiram is detectable at a detection limit of 5.88 × 10-11M with a high degree of sensitivity and repeatability.

Improving the Luminescence Performance of Monolayer MoS2 by Doping Multiple Metal Elements with CVT Method.

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) draw much attention as critical semiconductor materials for 2D, optoelectronic, and spin electronic devices. Although controlled doping of 2D semiconductors can also be used to tune their bandgap and type of carrier and further change their electronic, optical, and catalytic properties, this remains an ongoing challenge. Here, we successfully doped a series of metal elements (including Hf, Zr, Gd, and Dy) into the monolayer MoS2 through a single-step chemical vapor transport (CVT), and the atomic embedded structure is confirmed by scanning transmission electron microscope (STEM) with a probe corrector measurement. In addition, the host crystal is well preserved, and no random atomic aggregation is observed. More importantly, adjusting the band structure of MoS2 enhanced the fluorescence and the carrier effect. This work provides a growth method for doping non-like elements into 2D MoS2 and potentially many other 2D materials to modify their properties.

Hydrophilic magnetic Ti3C2Tx-based nanocomposite as an efficient boron adsorbent: Synthesis, characterization, and application.

It is widely recognized that wastewater containing boron is an environmental issue. Therefore, the development of adsorbents with excellent adsorption capacity, stability, and recyclability is essential in water treatment applications. A Fe3O4/PDA/Ti3C2Tx/PEI/DHHA nanocomposite has been prepared that can be used to separate and recover boric acid by adjusting the pH of the solution, based on the affinity theory of boric acid and cis-diol. Through series characterization, it was determined that the adsorbent possessed good magnetic properties, high hydrophilicity and high loading capacities. In this study, 4-formylphenylboronic acid (FPBA) was selected as the model compound. The nanocomposite exhibited an adsorption equilibrium time of 10 h and an adsorption capacity of 98.99 mg/g at pH = 8.5 and 25 °C. The Langmuir isothermal model and the quasi-secondary kinetic model are both appropriate for describing the adsorption process. Thermodynamic results suggest that adsorption is a spontaneous chemisorption process. Furthermore, the nanocomposite retains good regeneration performance after five adsorption-desorption cycles.

Clinical Interpretability of Deep Learning for Predicting Microvascular Invasion in Hepatocellular Carcinoma by Using Attention Mechanism.

Preoperative prediction of microvascular invasion (MVI) is essential for management decision in hepatocellular carcinoma (HCC). Deep learning-based prediction models of MVI are numerous but lack clinical interpretation due to their "black-box" nature. Consequently, we aimed to use an attention-guided feature fusion network, including intra- and inter-attention modules, to solve this problem. This retrospective study recruited 210 HCC patients who underwent gadoxetate-enhanced MRI examination before surgery. The MRIs on pre-contrast, arterial, portal, and hepatobiliary phases (hepatobiliary phase: HBP) were used to develop single-phase and multi-phase models. Attention weights provided by attention modules were used to obtain visual explanations of predictive decisions. The four-phase fusion model achieved the highest area under the curve (AUC) of 0.92 (95% CI: 0.84-1.00), and the other models proposed AUCs of 0.75-0.91. Attention heatmaps of collaborative-attention layers revealed that tumor margins in all phases and peritumoral areas in the arterial phase and HBP were salient regions for MVI prediction. Heatmaps of weights in fully connected layers showed that the HBP contributed the most to MVI prediction. Our study firstly implemented self-attention and collaborative-attention to reveal the relationship between deep features and MVI, improving the clinical interpretation of prediction models. The clinical interpretability offers radiologists and clinicians more confidence to apply deep learning models in clinical practice, helping HCC patients formulate personalized therapies.

Harnessing dual-energy CT for glycogen quantification: a phantom analysis.

Background: Non-invasive glycogen quantification in vivo could provide crucial information on biological processes for glycogen storage disorder. Using dual-energy computed tomography (DECT), this study aimed to assess the viability of quantifying glycogen content in vitro. Methods: A fast kilovolt-peak switching DECT was used to scan a phantom containing 33 cylinders with different proportions of glycogen and iodine mixture at varying doses. The virtual glycogen concentration (VGC) was then measured using material composition images. Additionally, the correlations between VGC and nominal glycogen concentration (NGC) were evaluated using least-square linear regression, then the calibration curve was constructed. Quantitative estimation was performed by calculating the linearity, conversion factor (inverse of curve slope), stability, sensitivity (limit of detection/limit of quantification), repeatability (inter-class correlation coefficient), and variability (coefficient of variation). Results: In all conditions, excellent linear relationship between VGC and NGC were observed (P<0.001, coefficient of determination: 0.989-0.997; residual root-mean-square error of glycogen: 1.862-3.267 mg/mL). The estimated conversion factor from VGC to NGC was 3.068-3.222. In addition, no significant differences in curve slope were observed among different dose levels and iodine densities. The limit of detection and limit of quantification had respective ranges of 6.421-15.315 and 10.95-16.46 mg/mL. The data demonstrated excellent scan-repeat scan agreement (inter-class correlation coefficient, 0.977-0.991) and small variation (coefficient of variation, 0.1-0.2%). Conclusions: The pilot phantom analysis demonstrated the feasibility and efficacy of detecting and quantifying glycogen using DECT and provided good quantitative performance with significant stability and reproducibility/variability. Thus, in the future, DECT could be used as a convenient method for glycogen quantification to provide more reliable information for clinical decision-making.

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.

OBJECTIVES: To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. METHODS: A total of 542 patients with clinical stage 0-I peripheral LUAD and with preoperative CT data of 1-mm slice thickness were included. Maximal solid size on axial image (MSSA) was evaluated by two chest radiologists. MSSA, volume of solid component (SV), and mass of solid component (SM) were evaluated by DL. Consolidation-to-tumor ratios (CTRs) were calculated. For ground glass nodules (GGNs), solid parts were extracted with different density level thresholds. The prognosis prediction efficacy of DL was compared with that of manual measurements. Multivariate Cox proportional hazards model was used to find independent risk factors. RESULTS: The prognosis prediction efficacy of T-staging (TS) measured by radiologists was inferior to that of DL. For GGNs, MSSA-based CTR measured by radiologists (RMSSA%) could not stratify RFS and OS risk, whereas measured by DL using 0HU (2D-AIMSSA0HU%) could by using different cutoffs. SM and SV measured by DL using 0 HU (AISM0HU% and AISV0HU%) could effectively stratify the survival risk regardless of different cutoffs and were superior to 2D-AIMSSA0HU%. AISM0HU% and AISV0HU% were independent risk factors. CONCLUSION: DL algorithm can replace human for more accurate T-staging of LUAD. For GGNs, 2D-AIMSSA0HU% could predict prognosis rather than RMSSA%. The prediction efficacy of AISM0HU% and AISV0HU% was more accurate than of 2D-AIMSSA0HU% and both were independent risk factors. CLINICAL RELEVANCE STATEMENT: Deep learning algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma. KEY POINTS: • Deep learning (DL) algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma (LUAD). • For GGNs, maximal solid size on axial image (MSSA)-based consolidation-to-tumor ratio (CTR) measured by DL using 0 HU could stratify survival risk than that measured by radiologists. • The prediction efficacy of mass- and volume-based CTRs measured by DL using 0 HU was more accurate than of MSSA-based CTR and both were independent risk factors.

Controllable Synthesis and Charge Density Wave Phase Transitions of Two-Dimensional 1T-TaS2 Crystals.

1T-TaS2 has attracted much attention recently due to its abundant charge density wave phases. In this work, high-quality two-dimensional 1T-TaS2 crystals were successfully synthesized by a chemical vapor deposition method with controllable layer numbers, confirmed by the structural characterization. Based on the as-grown samples, their thickness-dependency nearly commensurate charge density wave/commensurate charge density wave phase transitions was revealed by the combination of the temperature-dependent resistance measurements and Raman spectra. The phase transition temperature increased with increasing thickness, but no apparent phase transition was found on the 2~3 nm thick crystals from temperature-dependent Raman spectra. The transition hysteresis loops due to temperature-dependent resistance changes of 1T-TaS2 can be used for memory devices and oscillators, making 1T-TaS2 a promising material for various electronic applications.

High-Efficiency Miniaturized Ultrasonic Nebulization Sample Introduction System for Elemental Analysis of Microvolume Biological Samples by Inductively Coupled Plasma Quadrupole Mass Spectrometry.

Sensitive and high-throughput analysis of trace elements in volume-limited biological samples is highly desirable for clinical research and health risk assessments. However, the conventional pneumatic nebulization (PN) sample introduction is usually inefficient and not well-suited for this requirement. Herein, a novel high-efficiency (nearly 100% sample introduction efficiency) and low-sample-consumption introduction device was developed and successfully coupled with inductively coupled plasma quadrupole mass spectrometry (ICP-QMS). It consists of a micro-ultrasonic nebulization (MUN) component with an adjustable nebulization rate and a no-waste spray chamber designed based on fluid simulation. The proposed MUN-ICP-QMS could achieve sensitive analysis at a low sampling rate of 10 µL min-1 with an extremely low oxide ratio of 0.25% where the sensitivity is even higher comparing to PN (100 µL min-1). The characterization results indicate that the higher sensitivity of MUN is attributed to the smaller aerosol size, higher aerosol transmission efficiency, and improved ion extraction. In addition, it offers a fast washout (20 s) and reduced sample consumption (as low as 7 µL). The absolute LODs of the studied 26 elements by MUN-ICP-QMS are improved by 1-2 orders of magnitude compared with PN-ICP-QMS. The accuracy of the proposed method was validated by the analysis of human serum, urine, and food-related certified reference materials. Furthermore, preliminary results of serum samples from patients with mental illnesses demonstrated its potential in the field of metallomics.

Spatial and temporal regulation of homogeneous nucleation and crystal growth for high-flux electrochemical water softening.

Electrochemical softening is an effective technology for the treatment of circulating cooling water, but its hardness removal efficiency is limited because that nucleation and growth of scale crystals depended on cathode surface. In this study, a novel method was proposed to break through this limit via spatiotemporal management of nucleation and growth processes. A cube reactor was divided into cathodic chamber and anodic chamber via installing a sandwich structure module composed of mesh cathode, nylon nets, and mesh anode. Using this continuous-flowing electrochemical reactor, OH ̄ generated by water electrolysis was rapidly pushed away from cathode surface by water flow and hydrogen bubbles movement. As a result, a wide range of strongly alkaline regions was rapidly constructed in cathodic chamber to play a nucleation region, and homogeneous nucleation in liquid phase replaced heterogeneous nucleation on cathodic surface. Furthermore, the growth process of scale crystals in alkaline regions was monitored in situ. It took only 150 s of residence time to grow to 500 nm, which may be easily separated from water by a microfiltration membrane. With this new method, the precipitation rate was 290.8 g/(hˑm2) and corresponding energy consumption was 2.1 kW·h/kg CaCO3, both were superior to those reported values. Therefore, this study developed an efficient electrochemical softening method by spatial and temporal regulation of homogeneous nucleation and crystal growth processes.

Dietary Fibre Supplementation Improves Semen Production by Increasing Leydig Cells and Testosterone Synthesis in a Growing Boar Model.

Testicular development is imperative to spermatogenesis, and pre-puberty is the key period for testis development. This study, therefore, investigated the effects of fibre supplementation on testis development and its possible mechanism in a growing boar model. Thirty Yorkshire boars were randomly divided into a control group (Control) and a fibre group (Fibre) from day 0 to 90 after weaning, with three pigs per pen and five pens per treatment. Blood and testes were collected for analysis. Dietary fibre supplementation had no significant effect on growth performance, testicular volume, or libido but increased the semen production of boars. Boars fed with fibre had lower serum cholesterol (CHO) and low-density lipoprotein (LDL) levels compared to those on the Control diet; however, testicular CHO, triglyceride (TG), and LDL concentration in the Fibre group were significantly higher than the Control group (P < 0.01). Testicular histological analysis showed that seminiferous tubules and testicular germ cells of 120-day-old boars were densely arranged in the Fibre group, and the number of Leydig cells was significantly higher than that of the Control group (P < 0.001). Furthermore, the diet supplemented with fibre significantly decreased leptin, leptin receptor (Leptor), and luteinising hormone (LH) concentrations in boar serum (P < 0.05), whereas follicle-stimulating hormone (FSH) and testosterone concentrations were significantly increased (P < 0.05). Meanwhile, the expression of AMH, AMHR2, and SYCP3 genes related to proliferation and differentiation, and hormone-related genes STAR and SOCS3, were significantly up-regulated (P < 0.05). OCCLUDIN expression was up-regulated, whereas CDH2 expression was down-regulated. In conclusion, increased fibre intake during the pre-puberty period in growing boar is crucial for Leydig cell proliferation, up-regulating the expression of genes related to hormone synthesis and thereby promoting the secretion of testosterone and semen production.

Phenanthroline-imine ligands for iron-catalyzed alkene hydrosilylation.

Iron-catalyzed organic reactions have been attracting increasing research interest but still have serious limitations on activity, selectivity, functional group tolerance, and stability relative to those of precious metal catalysts. Progress in this area will require two key developments: new ligands that can impart new reactivity to iron catalysts and elucidation of the mechanisms of iron catalysis. Herein, we report the development of novel 2-imino-9-aryl-1,10-phenanthrolinyl iron complexes that catalyze both anti-Markovnikov hydrosilylation of terminal alkenes and 1,2-anti-Markovnikov hydrosilylation of various conjugated dienes. Specifically, we achieved the first examples of highly 1,2-anti-Markovnikov hydrosilylation reactions of aryl-substituted 1,3-dienes and 1,1-dialkyl 1,3-dienes with these newly developed iron catalysts. Mechanistic studies suggest that the reactions may involve an Fe(0)-Fe(ii) catalytic cycle and that the extremely crowded environment around the iron center hinders chelating coordination between the diene and the iron atom, thus driving migration of the hydride from the silane to the less-hindered, terminal end of the conjugated diene and ultimately leading to the observed 1,2-anti-Markovnikov selectivity. Our findings, which have expanded the types of iron catalysts available for hydrosilylation reactions and deepened our understanding of the mechanism of iron catalysis, may inspire the development of new iron catalysts and iron-catalyzed reactions.

Adaptor SH3BGRL drives autophagy-mediated chemoresistance through promoting PIK3C3 translation and ATG12 stability in breast cancers.

Acquired chemotherapy resistance is one of the main culprits in the relapse of breast cancer. But the underlying mechanism of chemotherapy resistance remains elusive. Here, we demonstrate that a small adaptor protein, SH3BGRL, is not only elevated in the majority of breast cancer patients but also has relevance with the relapse and poor prognosis of breast cancer patients. Functionally, SH3BGRL upregulation enhances the chemoresistance of breast cancer cells to the first-line doxorubicin treatment through macroautophagic/autophagic protection. Mechanistically, SH3BGRL can unexpectedly bind to ribosomal subunits to enhance PIK3C3 translation efficiency and sustain ATG12 stability. Therefore, inhibition of autophagy or silence of PIK3C3 or ATG12 can effectively block the driving effect of SH3BGRL on doxorubicin resistance of breast cancer cells in vitro and in vivo. We also validate that SH3BGRL expression is positively correlated with that of PIK3C3 or ATG12, as well as the constitutive occurrence of autophagy in clinical breast cancer tissues. Taken together, our data reveal that SH3BGRL upregulation would be a key driver to the acquired chemotherapy resistance through autophagy enhancement in breast cancer while targeting SH3BGRL could be a potential therapeutic strategy against breast cancer.Abbreviations: ABCs: ATP-binding cassette transporters; Act D: actinomycin D; ACTB/ß-actin: actin beta; ATG: autophagy-related; Baf A1: bafilomycin A1; CASP3: caspase 3; CHX: cycloheximide; CQ: chloroquine; Dox: doxorubicin; FBS: fetal bovine serum; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GEO: gene expression omnibus; GFP: green fluorescent protein; G6PD: glucose-6-phosphate dehydrogenase; GSEA: gene set enrichment analysis; IHC: immunochemistry; KEGG: Kyoto Encyclopedia of Genes and Genomes; MAP1LC3B/LC3B: microtubule-associated protein 1 light chain 3 beta; 3-MA: 3-methyladenine; mRNA: messenger RNA; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; SH3BGRL: SH3 domain binding glutamate-rich protein-like; SQSTM1/p62: sequestosome 1; ULK1: unc-51 like autophagy activating kinase 1.

Prediction of Early Treatment Response to Initial Conventional Transarterial Chemoembolization Therapy for Hepatocellular Carcinoma by Machine-Learning Model Based on Computed Tomography.

PURPOSE: The treatment response to initial conventional transarterial chemoembolization (cTACE) is essential for the prognosis of patients with hepatocellular carcinoma (HCC). This study explored and verified the feasibility of machine-learning models based on clinical data and contrast-enhanced computed tomography (CT) image findings to predict early responses of HCC patients after initial cTACE treatment. PATIENTS AND METHODS: Overall, 110 consecutive unresectable HCC patients who were treated with cTACE for the first time were retrospectively enrolled. Clinical data and imaging features based on contrast-enhanced CT were collected for the selection of characteristics. Treatment responses were evaluated based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) by postoperative CT examination within 2 months after the procedure. Python (version 3.70) was used to develop machine learning models. Least absolute shrinkage and selection operator (LASSO) algorithm was applied to select features with the impact on predicting treatment response after the first TACE procedure. Six machine learning algorithms were used to build predictive models, including XGBoost, decision tree, support vector machine, random forest, k-nearest neighbor, and fully convolutional networks, and their performances were compared using receiver operator characteristic (ROC) curves to determine the best performing model. RESULTS: Following TACE, 31 patients (28.2%) were described as responsive to TACE, while 72 patients (71.8%) were nonresponsive to TACE. Portal vein tumor thrombosis type, albumin level, and distribution of tumors within the liver were selected for predictive model building. Among the models, the RF model showed the best performance, with area under the curve (AUC), accuracy, sensitivity, and specificity of 0.802, 0.784, 0.904, and 0.480, respectively. CONCLUSION: Machine learning models can provide an accurate prediction of the early response of initial TACE treatment for HCC, which can help in individualizing clinical decision-making and modification of further treatment strategies for patients with unresectable HCC.

Silicon-Doped Argyrodite Solid Electrolyte Li6PS5I with Improved Ionic Conductivity and Interfacial Compatibility for High-Performance All-Solid-State Lithium Batteries.

Argyrodite-type sulfide solid electrolytes (SEs) Li6PS5X (X = Cl, Br, I) have attracted considerable interest lately by providing a promising lithium-ion transport capability for its application in all-solid-state lithium batteries (ASSLBs). However, other than Li6PS5Cl and Li6PS5Br, Li6PS5I shows poor ionic conductivity of 10-7 S cm-1, which is originated from the I-/S2- site ordered arrangement in its structure. Herein, we report a silicon-doped solid electrolyte Li6+xP1-xSixS5I in this sulfide class, which can remarkably increase the conductivity to 1.1 × 10-3 S cm-1 and lower the activation energy to 0.19 eV as a consequence of changing the structural unit in the argyrodite network. The Li6+xP1-xSixS5I solid electrolytes are employed in ASSLBs with Li(Ni0.8Mn0.1Co0.1)O2 (NCM-811) as cathode and Li metal as an anode to evaluate the electrochemical performance. With x = 0.55, the battery displays an initial discharge capacity of 105 mA h g-1 at a rate of 0.05C and achieves high Coulombic efficiency. Moreover, chemical reactions occurring on the interfaces of the NCM/SE and Li/SE in regard to the degradation of cell performance are also investigated.

Enhanced activation of peroxymonosulfate by nitrogen-doped graphene/TiO2 under photo-assistance for organic pollutants degradation: Insight into N doping mechanism.

Production of sulfate radical from peroxymonosulfate (PMS) activation by carbon-based catalysts is a promising strategy to degrade pollutants. However, the electron-transfer ability of carbon catalysts, which is critical in PMS activation, still needs to be improved. In this study, a novel photo-assisted PMS activation system (PPAS) was constructed on a nitrogen-doped graphene/TiO2 (NG/TiO2), in which the photogenerated electrons excited from TiO2 could be utilized by NG for enhanced PMS activation on it. Moreover, the N content was varied to firstly investigate the role of N doping on PPAS. Under photo-assistance, the NG/TiO2 displayed significantly enhanced PMS activation for removal of organic pollutants. 100% bisphenol A (BPA) can be removed within 1 h. The results show that the degradation kinetic constant of BPA by the NG/TiO2 PPAS was 24 times higher than that under PMS alone, and was 1.4 times higher than that of rGO/TiO2 PPAS. The singlet oxygen (1O2) and sulfate radical (SO4-) were the main reactive species in PPAS. The outstanding performance of NG/TiO2 system was ascribed to the two main reasons: on one hand, the N doping decreased the schottky barrier formed between NG and TiO2, which favored the electron transfer from TiO2 to NG. On the other hand, the N doping enhanced the adsorption and electron-transfer ability of NG towards PMS.